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Data Services Class Descriptions

Information, materials, and schedules for all currently offered Data Services classes
Getting Started with Python Pandas is an intermediate-to-advanced level class that offers basic strategies for reading, cleaning, and visualizing data with the Pandas Python library.
Software: Python, Jupyter Notebooks, Pandas
Duration: 120 min

Room description:

During the Fall 2021 semester, some tutorials are held remotely and require NYU sign on to access, while others are held in person, without a remote component. Please note the correct modality and location of the tutorial when registering

Prerequisites:
  • Familiarity with core Python objects types (lists, dictionaries, strings, numbers, functions)
  • Familiarity with common data storage file types such as CSV
  • Comfort with using Jupyter Notebooks for writing code
  • Preferred familiarity with data table structures and concepts like sorting, filtering, merging, and having common table keys
Skills Taught / Learning Outcomes:
  • Understand the building blocks of a Pandas dataframe
  • Know how to make a dataframe and how to load it with data
  • Filtering, selecting, and other common operations needed to focus on a subset of a dataframe
  • Updating values
  • Table joins and merges
  • Exporting a dataframe to a saved file
Class Materials: https://github.com/NYU-DataServices/startingpandas
Related Classes:
  • Introduction to Python
  • Data Cleaning Using OpenRefine
  • Data Visualization with Tableau
  • Introduction to Jupyter Notebooks
  • Introduction to Research Data Management
Additional Training Materials:

Data analysis with Python and Pandas [video]

Feedback: bit.ly/feedbackds

 

Upcoming sessions for this tutorial